Various devices have been proposed in our lives. While living among such devices, users enjoy desired information or services by manipulating the devices. Because of an increase in the number of devices themselves, an increase in the information that cannot be obtained without using devices, and so on, the importance of improving the manipulability of such interfaces is increasing year after year. In information devices (television sets, mobile phones, PDAs, etc.), for example, device manipulations are hitherto realized by selecting an manipulation option while watching a screen. As manipulation input means thereof, methods such as pressing a button, moving a cursor and making a confirmation, or manipulating a mouse while watching a screen have been used. However, it has been difficult to execute a manipulation when both hands are unavailable, due to tasks other than device manipulations, e.g., household chores, rearing of children, and driving an automobile.
In answer thereto, there are input means utilizing biometric signals from a user. Non-Patent Document 1 discloses a technique that utilizes an event-related potential of an electroencephalogram for distinguishing an option which a user wishes to select.
Specifically, options are randomly highlighted, and a positive component (P300 component) which appears in a time slot from 300 ms to 500 ms after a point in time that an option that the user wishes to select was highlighted is utilized to enable distinction as to wishing to select or not. According to this technique, even in a situation where both hands are full, or even in a situation where the user is unable to move his or her limbs due to an illness or the like, the user can select an option which they wish to select, whereby an interface for device manipulations, etc., can be realized.
Thus, conventionally, a menu selection based on an electroencephalogram has been realized by applying various processing to an electroencephalogram signal.    [Non-Patent Document 1] Emanuel Donchin and two others, “The Mental Prosthesis: Assessing the Speed of a P300-Based Brain-Computer Interface”, IEEE TRANSACTIONS ON REHABILITATION ENGINEERING, Vol. 8, No. 2, June 2000